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International Journal of Advanced Computer Science and Applications(IJACSA), Volume 10 Issue 1, 2019.
Abstract: Mobile ad hoc network (MANET) is a set of independent mobile nodes, which connect to each other over a wireless channel without any centralized infrastructure, nor integrated security. MANET is a weak target to many Denial of Service (DOS) attacks, which seriously harms its functionality and connectivity. A black hole attack is a type of DOS attack, where the malevolent node tries to get all the data packets from a source node by sending fabricated fake route reply (RREP) packet, falsely pretending that it possesses the shortest path towards the destination node, and then drops all the packets it receives. In this paper, the AODV (Ad-hoc on-demand distance vector) routing protocol is improved by incorporating an efficient and simple mechanism to mitigate black hole attacks. Mechanism to detect black hole attacks from MANET (MDBM) uses fake route request (RREQ) packets with an unreal destination address in order to detect black hole nodes prior to the actual routing process. Simulation experiment conducted has verified the performance of the proposed detection and prevention scheme. The results demonstrated that the proposed mechanism performed well in terms of Packet Delivery Ratio, End-to-End Delay and Throughput under black hole attack.
Muhammad Salman Pathan, Jingsha He, Nafei Zhu, Zulfiqar Ali Zardari, Muhammad Qasim Memon and Aneeka Azmat, “An Efficient Scheme for Detection and Prevention of Black Hole Attacks in AODV-Based MANETs” International Journal of Advanced Computer Science and Applications(IJACSA), 10(1), 2019. http://dx.doi.org/10.14569/IJACSA.2019.0100132
@article{Pathan2019,
title = {An Efficient Scheme for Detection and Prevention of Black Hole Attacks in AODV-Based MANETs},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2019.0100132},
url = {http://dx.doi.org/10.14569/IJACSA.2019.0100132},
year = {2019},
publisher = {The Science and Information Organization},
volume = {10},
number = {1},
author = {Muhammad Salman Pathan and Jingsha He and Nafei Zhu and Zulfiqar Ali Zardari and Muhammad Qasim Memon and Aneeka Azmat}
}
Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.